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Parametric matrix models

Nature Communications
We present a general class of machine learning algorithms called parametric matrix models. In contrast with most existing machine learning models that imitate the biology of neurons, parametric matrix models use matrix equations that emulate physical ...
Patrick Cook, Danny Jammooa, Morten Hjorth-Jensen, Daniel D. Lee, Dean Lee   +4 more
doaj   +4 more sources

Evaluation of goodness of fit of semiparametric and parametric models in analysis of factors associated with length of stay in neonatal intensive care unit [PDF]

Clinical and Experimental Pediatrics, 2020
Background Length of stay is a significant indicator of care effectiveness and hospital performance. Owing to the limited number of healthcare centers and facilities, it is important to optimize length of stay and associated factors.
Fatemeh Kheiry, Sadegh Kargarian-Marvasti, Sima Afrashteh, Abolfazl Mohammadbeigi, Nima Daneshi, Salma Naderi, Seyed Hossein Saadat   +6 more
doaj   +2 more sources

Analysis of parametric and non-parametric option pricing models

Heliyon, 2022
In this paper, a closed-form analytical solution of option price under the Bi-Heston model is derived. Through empirical analysis, the advantages and disadvantages of the parametric pricing model are compared and analysed with those of the non-parametric
Qiang Luo, Zhaoli Jia, Hongbo Li, Yongxin Wu   +3 more
doaj   +3 more sources

Comparing of cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes

Journal of Research in Medical Sciences, 2017
Background: Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox ...
Sadegh Kargarian-Marvasti, Shahnaz Rimaz, Jamileh Abolghasemi, Iraj Heydari   +3 more
doaj   +2 more sources

Parametric model embedding

Computer Methods in Applied Mechanics and Engineering, 2023
Paper submitted to Computer Methods in Applied Mechanics and ...
Serani Andrea, Diez Matteo
openaire   +2 more sources

Deep Neural Networks for Analysis of Microscopy Images—Synthetic Data Generation and Adaptive Sampling

Crystals, 2021
The analysis of microscopy images has always been an important yet time consuming process in materials science. Convolutional Neural Networks (CNNs) have been very successfully used for a number of tasks, such as image segmentation.
Patrick Trampert, Dmitri Rubinstein, Faysal Boughorbel, Christian Schlinkmann, Maria Luschkova, Philipp Slusallek, Tim Dahmen, Stefan Sandfeld   +7 more
doaj   +1 more source

Ontology-Based Semantic Conceptualisation of Historical Built Heritage to Generate Parametric Structured Models from Point Clouds

Applied Sciences, 2021
Nowadays, cultural and historical built heritage can be more effectively preserved, valorised and documented using advanced geospatial technologies. In such a context, there is a major issue concerning the automation of the process and the extraction of ...
Elisabetta Colucci, Xufeng Xing, Margarita Kokla, Mir Abolfazl Mostafavi, Francesca Noardo, Antonia Spanò   +5 more
doaj   +1 more source

Comparing Survival Extrapolation within All-Cause and Relative Survival Frameworks by Standard Parametric Models and Flexible Parametric Spline Models Using the Swedish Cancer Registry [PDF]

Medical Decision Making
Enoch Yi-Tung Chen, Chia-Ni Lin, Jung-Der Wang   +2 more
exaly   +2 more sources

PGD based meta modelling of a lithium-ion battery for real time prediction

Frontiers in Materials, 2023
Despite the existence of computationally efficient tools, the effort for parametric investigations is currently high in industry. In this paper, within the context of Li-Ion batteries, an efficient meta-modelling approach based on the Proper Generalized ...
Alexander Schmid, Angelo Pasquale, Angelo Pasquale, Christian Ellersdorfer, Victor Champaney, Victor Champaney, Marco Raffler, Simon Guévelou, Stephan Kizio, Mustapha Ziane, Florian Feist, Francisco Chinesta, Francisco Chinesta, Francisco Chinesta   +13 more
doaj   +1 more source

Retrospective Post-Hospitalisation COVID-19 Mortality Risk Assessment of Patients in South Africa

European Journal of Investigation in Health, Psychology and Education, 2023
Background: This study explores the determinants impacting the mortality risk of COVID-19 patients following hospitalisation within South Africa’s Limpopo province. Methods: Utilising a dataset comprising 388 patients, the investigation employs a frailty
Alexander Boateng, Daniel Maposa, Reshoketswe Mokobane   +2 more
doaj   +1 more source